The present invention relates to medical imaging arts. In particular, it relates to the imaging, tracking, and displaying of neural fibers and fiber bundles by diffusion tensor magnetic resonance imaging (DT-MRI), and will be described with particular reference thereto. However, the invention will also find application in conjunction with tracking and graphical rendering of other types of fibrous structures, as well as with other imaging modalities.
Nerve tissue in human beings and other mammals includes neurons with elongated axonal portions arranged to form neural fibers or fiber bundles along which electrochemical signals are transmitted. In the brain, for example, functional areas defined by very high neural densities are typically linked by structurally complex neural networks of axonal fiber bundles. The axonal fiber bundles and other fibrous material are substantially surrounded by other tissue.
Diagnosis of neural diseases, planning for brain surgery, and other neurologically related clinical activities, as well as research studies on brain function, can benefit from non-invasive imaging and tracking of the axonal fibers and fiber bundles. In particular, diffusion tensor magnetic resonance imaging (DT-MRI) has been shown to provide sufficient image contrast to image axonal fiber bundles. In the DT-MRI technique, diffusion-sensitizing magnetic field gradients are applied in the excitation/imaging sequence so that the magnetic resonance images include contrast related to the diffusion of water or other fluid molecules. By applying the diffusion gradients in selected directions during the excitation/imaging sequence, diffusion weighted images are acquired from which apparent diffusion tensor coefficients are obtained for each voxel location in image space.
Fluid molecules diffuse more readily along the direction of the axonal fiber bundle as compared with directions partially or totally orthogonal to the fibers. Hence, the directionality and anisotropy of the apparent diffusion coefficients tend to correlate with the direction of the axonal fibers and fiber bundles.
Extraction of fibrous structure information from DT-MRI images is computationally intensive, with processing times typically extending from several tens of minutes to an hour or more for clinically valuable images. In a clinical setting, it is unrealistic to expect a subject to remain motionless for these extended periods of time. Even with movement restricting devices, the subject is not totally immobile, and can still move enough to create distortions in resultant images. Additionally, distortions apart from subject motion can occur, degrading resultant images.
The present invention contemplates an improved apparatus and method that overcomes the aforementioned limitations and others.
In accordance with one aspect of the present invention, a method of diffusion-weighted magnetic resonance imaging is provided. A plurality of static image representations and a plurality of diffusion image representations, with each of a plurality of diffusion weightings, of the same region of interest in a subject are generated. The static images and the like diffusion weighted images are aligned. Images that differ from other static and like diffusion weighted images are rejected. The non-rejected static images and the non-rejected diffusion weighted images with like diffusion weightings are combined. The combined static and diffusion-weighted images are analyzed to image an isotropic structure.
In accordance with another aspect of the present invention, a method of diffusion tensor magnetic resonance imaging is provided. A static and a plurality of differently diffusion weighted magnetic resonance data sets are collected, each representing the same spatial region within a subject. The collecting step is repeated to generate a plurality of static data sets and a plurality of diffusion weighted data sets corresponding to each diffusion weighting. The data sets are reconstructed into image representations. The image representations are adjusted for better spatial conformity. Static images that fail to exhibit a predetermined similarity to other static images are rejected. Similarly, diffusion weighted images that fail to exhibit a predetermined similarity to other diffusion-weighted images of like diffusion weighting are rejected. The remaining static images and like diffusion weighted images are combined. In at least a region of interest, apparent diffusion coefficient tensors are calculated for each volume of a region of interest of the remaining images. Eigenvalues and Eigenvectors are extracted from the diffusion coefficient tensors. An anisotropic structure is tracked with the Eigenvalues and Eigenvectors. A human-readable display of the tracked anisotropic structure is generated.
In accordance with another aspect of the present invention, a magnetic resonance apparatus is provided. A main magnet assembly generates a substantially uniform main magnetic field through an imaging region. A gradient coil assembly superimposes gradient magnetic fields on the main magnetic field. A radio frequency coil assembly transmits radio frequency pulses into the imaging region. A radio frequency receiver receives and demodulates magnetic resonance signals from the imaging region. A data memory stores static and diffusion weighted data sets of a common region of a subject in the imaging region. A reconstruction processor reconstructs the data sets into static and diffusion weighted images. A comparator compares the static images with each other and like diffusion weighted images with each other. An image rejection processor discards images dissimilar to other like diffusion weighted and static images by more than a predetermined threshold. An image combining means combines the remaining static and diffusion weighted images into combined static and diffusion weighted images. A diffusion analysis processor (1) calculates a diffusion tensor coefficient from the combined images for each voxel of at least a region of interest, (2) creates Eigenvectors from the diffusion tensors, and (3) tracks an anisotropic structure with the Eigenvectors. A video processor and monitor generate a human-viewable display of the tracked anisotropic structure.
One advantage of the present invention resides in more accurate diffusion data.
Another advantage of the present invention resides in a reduced occurrence of imaging artifacts.
Yet another advantage of the present invention resides in increased signal to noise.
Numerous additional advantages and benefits of the present invention will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiment.